aarya

PyPI

Validates the existence of registered accounts across social & shopping platforms and extracts rich identity intelligence (Names, Photos, IDs).

Versions collected1

Direct dependencies5From release 1.0.9

Last observed20 Oct, 17:02 UTC

README

Version 1.0.9 documentation

Aarya (आर्य)

Email address to digital footprint for OSINT

Aarya is an OSINT tool that validates the existence of email addresses across social media, shopping, and professional platforms (e.g. Instagram, Amazon, Spotify) and extracts rich metadata like Google Map contributions, reviews and account creation dates for proton mail.

Aarya Demo

🚀 Features

Deep Analysis: Goes beyond simple "Yes/No" results to extract rich metadata like Google Maps reviews, Profile Pictures, Gaia IDs, and ProtonMail key creation dates.
Full Visibility: Reports positive hits, negative results, rate limits, and errors explicitly so you never miss a detail.
Smart Stealth: Automatically fetches the latest real-world User-Agents from the web to bypass simple bot detection filters.
Elegant UI: Professional, minimalist CLI design with responsive tables and clean link wrapping.

⚠️ Disclaimer

Aarya is designed for educational purposes, authorized security research, and personal digital footprint analysis only.

The developers are not responsible for any misuse of this tool. Scanning email addresses that do not belong to you or without the owner's explicit consent may violate privacy laws or platform Terms of Service in your jurisdiction. Use responsibly.

📦 Installation

Option 1: Install via PyPI (Recommended)

It is recommended to use a virtual environment to prevent conflicts.

Linux/macOS:

python -m venv .venv
source .venv/bin/activate
pip install aarya

Windows:

python -m venv .venv
.venv\Scripts\activate
pip install aarya

Option 2: Install from Source (Development)

If you want the latest features or updates directly from the repository:

git clone https://github.com/forshaur/aarya.git
cd aarya
pip install .

🛠 Usage

Basic Scan:

aarya target@example.com

Save Results:

aarya target@example.com -o results.json

🔍 Use Cases in Recon & Intel

1. Verification & Validation

Confirm if a target email is active. A "ghost" email (no accounts anywhere) is a high-risk indicator for fraud or burner accounts, whereas an email with established accounts verifies the identity exists.

Aarya helps Red Teamers map the digital footprint of a target. Knowing a target uses Duolingo or Wattpad allows for highly tailored phishing pretexts (e.g., "Your Duolingo streak is in danger" vs generic corporate emails).

3. Identity Correlation

By extracting unique identifiers like the Google Gaia ID or ProtonMail public key date, Aarya helps correlate an email address with real-world timelines, locations, and other digital identities across the web.

4. Credibility of Credential Reuse (Post-Exploitation)

If a target's password is compromised (via phishing or a data breach) for one verified platform, Aarya provides a precise roadmap of other active services where that same password might be reused, highlighting critical risks for credential stuffing attacks.

5. Corporate OpSec Auditing

Security teams can scan corporate email domains to detect "Shadow IT" or policy violations. Discovering that an employee used their official name@company.com address to sign up for Instagram or Amazon highlights potential attack surfaces and credential leakage risks.

6. OSINT Pivot Points

Aarya acts as a signpost for deeper investigation. A confirmed Google account signals an investigator to search for public Maps reviews or Photos. A confirmed Instagram account invites a search for public profile associated with that email. The tool identifies where to look next for public data.

7. Credibility Analysis (Anti-Fraud)

In fraud investigations, account age acts as a trust signal. An email address linked to a ProtonMail key created 3 years ago or a Google account with Maps contributions from 2019 is far more likely to be legitimate than a "fresh" email with absolutely no digital footprint.

🆚 Aarya vs. Holehe

During development of this tool I came to know that another great tool was already there which was similar to Aarya.

here is why Aarya outperforms.

Feature	Holehe	Aarya
Primary Output	Email Existence (True/False)	Identity Intelligence (Real Names, Photos, Maps Reviews)
Reliability	Prone to False Negatives and >50% modules don't work	High (Explicitly detects Rate Limits vs. Not Found)
Stealth	Static Headers	Dynamic (Auto-fetches latest User-Agents)
Focus	Quantity (120+ Sites)	Quality (Deep scans of High-Value Targets)
UI/UX	Basic CLI	Modern (Rich Tables, Clickable Links, Summary Panels)

🤝 Contributing

Contributions are welcome! If you want to add a new module (e.g., Pinterest, Adobe), please fork the repository and submit a Pull Request.

📜 License

This project is licensed under the GNU General Public License v3.0. See the LICENSE file for details.

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Versions 1

Collected releases

Version	Published	Direct dependencies	Open version
1.0.9	30 Jan 2026	5

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forshaur/aarya

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Also add information on how to contact you by electronic and paper mail. If the program does terminal interaction, make it output a short notice like this when it starts in an interactive mode: <program> Copyright (C) <year> <name of author> This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. This is free software, and you are welcome to redistribute it under certain conditions; type `show c' for details. The hypothetical commands `show w' and `show c' should show the appropriate parts of the General Public License. Of course, your program's commands might be different; for a GUI interface, you would use an "about box". You should also get your employer (if you work as a programmer) or school, if any, to sign a "copyright disclaimer" for the program, if necessary. For more information on this, and how to apply and follow the GNU GPL, see <https://www.gnu.org/licenses/>. The GNU General Public License does not permit incorporating your program into proprietary programs. If your program is a subroutine library, you may consider it more useful to permit linking proprietary applications with the library. If this is what you want to do, use the GNU Lesser General Public License instead of this License. But first, please read <https://www.gnu.org/licenses/why-not-lgpl.html>.
Collected versions: 1
Source: PyPI

PACKAGE URL

pkg:pypi/aarya

Project links

Registry Bug Tracker Homepage

Source & dates

Source modified: Unknown
First observed: 20 Oct 2026
Last observed: 20 Oct, 17:02 UTC

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